In this blog we will discuss three ways of doing your chatbot evaluation by using:
You have a chatbot up and running, offering help to your customers. But how do you know whether the help you are providing is correct or not? Chatbot evaluation can be complex, especially because it is affected by many factors.
We have gathered some ideas based on our experience in helping our clients improve their bots:
All these steps help us measure the usefulness of our chatbots or chatbot training datasets.
You can use any of them to evaluate the Free Dataset we offer, created with our Multilingual Synthetic Data technology, centered on Customer Support: feel free to download it here and give us your feedback!
For more information, visit our website and follow Bitext on Twitter or LinkedIn.
Bitext introduced the Copilot, a natural language interface that replaces static forms with a conversational,…
Automating Online Sales with a New Breed of Copilots. The next generation of GenAI Copilots…
GPT and other generative models tend to provide disparate answers for the same question. Having…
ChatGPT has major flaws that prevent it from becoming a useful tool in industries like…
If data is the oil of the AI industry, we are running out of data…
Fine-Tuning LLMs with Bitext's Hybrid Datasets: How AI Text Generation is Revolutionizing Conversational AI